The amount of information contained in documents is rapidly increasing. There are many industries such as law, education, journalism, politics, economics, or the like that may benefit from rapid and low-cost document analysis. Yet even with recent advances in artificial intelligence and computing, manual analysis still provides the best results for many document analysis tasks that involve subjective judgment and expert knowledge. However, the cost and relatively slow speed of manual, human analysis makes it effectively impossible or impracticable to perform document analysis at the scale, speed, and cost desired in many industries.
“Offshoring” to take advantage of lower costs may allow the hiring of a larger number of people to analyze documents at a lower price per hour of labor. Even so, there is a lower bound on costs and an upper bound on throughput. For example, analyzing a corpus of a million 30-page text documents overnight would be impossible using only human analysis. Automated document analysis using computers is much quicker than human analysis and performs at much lower cost. However, for analytical tasks involving subjective judgment, computers perform much worse than humans. Thus, devices and methods that can analyze documents in a way that emulates human analysis will have broad application across many different industries. Additionally, devices and methods that can analyze documents using unified rules may provide a more consistent analysis. For example, human analysis may include subjective differences when analyzing documents, which may provide for less useful results.